System and method for classifying human and non-human traffic using behavior authenticity

Abstract

The method and system for performing a completely automated public Turing test to tell computers and humans apart (CAPTCHA). The method comprises receiving by a server a request from a service server to initiate a CAPTCHA of a user node; generating an image of a path; generating at least one target to be placed upon the path; generating an object to be placed at a start point of the path; sending the generated path, the at least one generated target, and the object as a CAPTCHA challenge to the user node for display thereon; receiving, by the server, data respective of motion of the object with respect to the path and the at least one generated target; and issuing, based on analysis of the data received data, a pass indication upon determination that the user node is operative by a human.

What is claimed is: 
     
       1. A method for performing a completely automated public Turing test to tell computers and humans apart (CAPTCHA), comprising:
 receiving by a server a request from a service server to initiate a CAPTCHA of a user node; 
 generating, by the server, an image of a path; 
 generating, by the server, at least one target to be placed upon the path in the image; 
 generating, by the server, an object to be placed at a start point of the path in the image; 
 sending the generated image of the path, the at least one generated target, and the object as a CAPTCHA challenge to the user node for display thereon; 
 receiving, by the server, data based on motion of the object with respect to the path and the at least one generated target; and 
 issuing, based on analysis of the received data, a pass indication upon determination that the user node is operative by a human. 
 
     
     
       2. The method of  claim 1 , wherein issuing the pass indication occurs upon determination that a predetermined number of successful pass over a target have occurred. 
     
     
       3. The method of  claim 1 , further comprising:
 issuing, based on analysis of the received data, a fail indication upon determination that the user node is operative by a bot. 
 
     
     
       4. The method of  claim 3 , wherein issuing the fail indication occurs upon determination that at least one pass over a target has failed. 
     
     
       5. The method of  claim 3 , further comprising:
 prior to sending a fail indication, checking whether it is permissible to repeat a CAPTCHA challenge; and 
 when it is permissible to repeat a CAPTCHA challenge, re-generating an image of a path. 
 
     
     
       6. The method of  claim 3 , further comprising:
 sending the user node a fail indication. 
 
     
     
       7. The method of  claim 3 , further comprising:
 sending the service server a fail indication. 
 
     
     
       8. The method of  claim 1 , wherein the service server is at least one of: a website, a computer program, an interactive device, and an interactive application. 
     
     
       9. The method of  claim 1 , wherein the image of the path comprises at least one of: a horizontal section, a vertical section, an inclines section, a declined section, and a curved section. 
     
     
       10. The method of  claim 1 , wherein the object is one of: a two-dimensional image, and a three-dimensional image. 
     
     
       11. The method of  claim 1 , wherein the object is one of: a geometric shape and an illustrated character. 
     
     
       12. The method of  claim 1 , wherein the analysis of the received data further comprises:
 analyzing the received data based on motion of the object with respect to the path and the at least one target. 
 
     
     
       13. The method of  claim 1 , wherein the analysis of the received data further comprises: applying a predetermined rule-based analysis. 
     
     
       14. The method of  claim 1 , wherein the analysis of the received data further comprises: analyzing the data using a machine learning model. 
     
     
       15. The method of  claim 14 , further comprising:
 training the machine learning model using a training dataset, wherein the dataset enables detection of differences between a human interaction with the CAPTCHA challenge and a computer interaction with the CAPTCHA challenge. 
 
     
     
       16. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process for performing a completely automated public Turing test to tell computers and humans apart (CAPTCHA), the processing comprising:
 receiving by a server a request from a service server to initiate a CAPTCHA of a user node; 
 generating, by the server, an image of a path; 
 generating, by the server, at least one target to be placed upon the path in the image; 
 generating, by the server, an object to be placed at a start point of the path in the image; 
 sending the generated image of the path, the at least one generated target, and the object as a CAPTCHA challenge to the user node for display thereon; 
 receiving, by the server, data based on motion of the object with respect to the path and the at least one generated target; and 
 issuing, based on analysis of the received data, a pass indication upon determination that the user node is operative by a human. 
 
     
     
       17. A system for performing a completely automated public Turing test to tell computers and humans apart (CAPTCHA), comprising:
 a processing circuitry; and 
 a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system for: 
 receive by a server a request from a service server to initiate a CAPTCHA of a user node; 
 generate, by the server, an image of a path; 
 generate, by the server, at least one target to be placed upon the path in the image; 
 generate, by the server, an object to be placed at a start point of the path in the image; 
 send the generated image of the path, the at least one generated target, and the object as a CAPTCHA challenge to the user node for display thereon; 
 receive, by the server, data based on motion of the object with respect to the path and the at least one generated target; and 
 issue, based on analysis of the received data, a pass indication upon determination that the user node is operative by a human. 
 
     
     
       18. The system of  claim 17 , wherein the system is further configured to:
 issue the pass indication occurs upon determination that a predetermined number of successful pass over a target have occurred. 
 
     
     
       19. The system of  claim 17 , wherein the system is further configured to:
 issue, based on analysis of the data received, a fail indication upon determination that the user node is operative by a bot. 
 
     
     
       20. The system of  claim 19 , wherein the system is further configured to:
 issue the fail indication occurs upon determination that at least one pass over a target has failed.